Triple
T25844994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Former Zhao |
E651040
|
entity |
| Predicate | relationshipToLaterZhao |
P60493
|
FINISHED |
| Object | predecessor state |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: predecessor state | Statement: [Former Zhao, relationshipToLaterZhao, predecessor state]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToLaterZhao Context triple: [Former Zhao, relationshipToLaterZhao, predecessor state]
-
A.
laterRelationshipWith
Indicates that one entity has a relationship with another that occurs at a later time relative to some reference point or prior relationship.
-
B.
laterRelationWith
chosen
Indicates that one entity stands in a temporal relationship to another such that it occurs or exists at a later time than the other.
-
C.
relationshipToHannah
Indicates the specific type of relationship or connection that an entity has to Hannah.
-
D.
relationshipToSeongGiHun
Indicates the type or nature of the relationship an entity has with Seong Gi-hun.
-
E.
historicalRelationship
Indicates a relationship that existed between entities in the past, often tied to a specific historical period, context, or event.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e7ab38086081908f3a8e7e0c6efd83 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fd4d1854988190be093b103a681798 |
completed | May 8, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69fd4c8d1a188190897c24527337814a |
completed | May 8, 2026, 2:38 a.m. |
Created at: April 22, 2026, 7:52 a.m.